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Roberto Vega
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Journal Articles
- 2017
- [j3]Roberto Vega, Touqir Sajed, Kory Wallace Mathewson, Kriti Khare, Patrick M. Pilarski, Russell Greiner, Gildardo Sánchez-Ante, Javier Mauricio Antelis:
Assessment of feature selection and classification methods for recognizing motor imagery tasks from electroencephalographic signals. Artif. Intell. Res. 6(1): 37-51 (2017) - 2016
- [j2]Ricardo Ocampo-Vega, Gildardo Sánchez-Ante, Marco A. de Luna, Roberto Vega, Luis E. Falcón-Morales, Humberto Sossa:
Improving pattern classification of DNA microarray data by using PCA and logistic regression. Intell. Data Anal. 20(s1): S53-S67 (2016) - 2015
- [j1]Roberto Vega, Gildardo Sánchez-Ante, Luis Falcón-Morales, Humberto Sossa, Elizabeth Guevara:
Retinal vessel extraction using Lattice Neural Networks with dendritic processing. Comput. Biol. Medicine 58: 20-30 (2015)
Conference and Workshop Papers
- 2021
- [c8]Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner:
Sample efficient learning of image-based diagnostic classifiers via probabilistic labels. AISTATS 2021: 739-747 - [c7]Rajshree Daulatabad, Roberto Vega, Jacob L. Jaremko, Jeevesh Kapur, Abhilash Rakkunedeth Hareendranathan, Kumaradevan Punithakumar:
Integrating User-Input into Deep Convolutional Neural Networks for Thyroid Nodule Segmentation. EMBC 2021: 2637-2640 - [c6]Atefeh Shahroudnejad, Roberto Vega, Amir Forouzandeh, Sharanya Balachandran, Jacob L. Jaremko, Michelle Noga, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Kumaradevan Punithakumar:
Thyroid Nodule Segmentation and Classification Using Deep Convolutional Neural Network and Rule-based Classifiers. EMBC 2021: 3118-3121 - 2018
- [c5]Roberto Vega, Russell Greiner:
Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data. MLCN/DLF/iMIMIC@MICCAI 2018: 32-39 - 2015
- [c4]Leonardo Ojeda, Roberto Vega, Luis Eduardo Falcón, Gildardo Sánchez-Ante, Humberto Sossa, Javier Mauricio Antelis:
Classification of Hand Movements from Non-invasive Brain Signals Using Lattice Neural Networks with Dendritic Processing. MCPR 2015: 23-32 - 2014
- [c3]Ricardo Ocampo-Vega, Marco A. de Luna, Roberto Vega, Gildardo Sánchez-Ante, Luis Falcón-Morales, Humberto Sossa:
Pattern Analysis in DNA Microarray Data through PCA-Based Gene Selection. CIARP 2014: 532-539 - 2013
- [c2]Roberto Vega, Elizabeth Guevara, Luis Eduardo Falcón, Gildardo Sánchez-Ante, Humberto Sossa:
Blood Vessel Segmentation in Retinal Images Using Lattice Neural Networks. MICAI (1) 2013: 532-544 - [c1]Héctor Quintián-Pardo, Roberto Vega, Vicente Vera, Ignacio Aliaga, Cristina González Losada, Emilio Corchado, Fanny Klett:
Soft Computing Techniques for Skills Assessment of Highly Qualified Personnel. SOCO-CISIS-ICEUTE 2013: 669-678
Informal and Other Publications
- 2023
- [i5]Roberto Vega, Zehra Shah, Pouria Ramazi, Russell Greiner:
Modeling and Forecasting COVID-19 Cases using Latent Subpopulations. CoRR abs/2302.04829 (2023) - 2022
- [i4]Roberto Vega, Russell Greiner:
Domain-shift adaptation via linear transformations. CoRR abs/2201.05282 (2022) - [i3]Gholamali Aminian, Roberto Vega, Omar Rivasplata, Laura Toni, Miguel R. D. Rodrigues:
Semi-Counterfactual Risk Minimization Via Neural Networks. CoRR abs/2209.07148 (2022) - 2021
- [i2]Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner:
Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels. CoRR abs/2102.06164 (2021) - [i1]Roberto Vega, Leonardo Flores, Russell Greiner:
SIMLR: Machine Learning inside the SIR model for COVID-19 Forecasting. CoRR abs/2106.01590 (2021)
Coauthor Index
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